Many aspects of the physiological stress related to the exposure to the hyperbaric environment have been studied, but no research has been made to evaluate the impacts of scuba diving on heart rate variability (HRV). We investigated the effects of a simulated dive to 557 KPa (45 meters of salt water) for a 30-minute bottom time on the frequency and time domains estimators of HRV. Electrocardiogram records were obtained with superficial electrodes for 30 minutes before the simulated dive and, subsequently, for one hour after the dive. Each of these time-series was then subdivided into non-overlapping windows of 256 consecutive R-R in- tervals. A control group was submitted to the same proto- col, breathing the same gases used in the simulated dive, while not being exposed to the hyperbaric environment. In the control group we observed a significant increase in SDNN (the square root of the variance of the R–R intervals), RMSSD (the square root of the mean squared differences of successive R-R intervals), and in two bands (high and low) of the power spectrum of frequencies. The subjects in the simulated dive presented only an increase in the low frequency estimator without any further relevant changes in other estimators of HRV. This study suggests that the low frequency increase without concomitant high frequency increase might be an indicator of the physiological stress caused by decom- pression and that such a dissimilarity in responses might be correlated to the dive-related impairment of the endothelial function.

The purpose of this study was to analyze the correlation between decompressionrelated physiological stress markers, given by inflammatory processes and immune system activation and changes in Heart Rate Variability, evaluating whether Heart Rate Variability can be used to estimate the physiological stress caused by the exposure to hyperbaric environments and subsequent decompression. A total of 28 volunteers participated in the experimental protocol. Electrocardiograms were performed; blood samples were obtained for the quantification of red cells, hemoglobin, hematocrit, neutrophils, lymphocytes, platelets, aspartate transaminase (AST), alanine aminotransferase (ALT), and for immunophenotyping and microparticles (MP) research through Flow Cytometry, before and after each experimental protocol from each volunteer. Also, myeloperoxidase (MPO) expression and microparticles (MPs) deriving from platelets, neutrophils and endothelial cells were quantified. Negative associations between the standard deviation of normal-to-normal intervals (SDNN) in the time domain, the High Frequency in the frequency domain and the total number of circulating microparticles was observed (p-value = 0.03 and p-value = 0.02, respectively). The pre and post exposure ratio of variation in the number of circulating microparticles was negatively correlated with SDNN (p-value = 0.01). Additionally, a model based on the utilization of Radial Basis Function Neural Networks (RBF-NN) was created and was able to predict the SDNN ratio of variation based on the variation of specific inflammatory markers (RMSE = 0.06).